R Notebook
Analysis and visualisation of spatial transcriptomics data. Generally followed this Seurat workflow.
Load libraries
library(UCell)
Loading required package: data.table
data.table 1.14.8 using 12 threads (see ?getDTthreads). Latest news: r-datatable.com
Attaching package: ‘data.table’
The following objects are masked from ‘package:dplyr’:
between, first, last
Loading required package: MatrixLoad merged liver slices and set identity
sobj <- readRDS("../spatial/merged_spatial_sobj.RDS")
Idents(sobj) <- "SCT_snn_res.0.2"Visualise clusters on spatial plot
plot1 <- SpatialDimPlot(sobj, alpha = 0.7, images = 'slice1') & NoLegend()plot2 <- SpatialDimPlot(sobj, alpha = 0.7, images = 'slice1.1') +
labs(fill = "Cluster")plot1 + plot2
pdf("./figures/spatial/merged_dimPlot_UMAP.pdf")plot1 + plot2
dev.off()png
2 
Visualise features on spatial plot
Calculate markers
all.markers <- FindAllMarkers(sobj, only.pos = TRUE,
min.pct = 0.25,
logfc.threshold = 0.25,
recorrect_umi = FALSE)
Calculating cluster 0
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|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=01s Create zonation scores using top 30 genes from periportal and pericentral clusters (like Tallulah’s paper)
cv_genes
[1] "FETUB" "HMGCS1" "CYP2E1" "GLUD1;GLUD2" "CYP1A2" "RGN" "INMT"
[8] "COMT" "FDPS" "SPR-1" Format for UCell
mySigs <- list()
mySigs$Periportal <- pp_genes
mySigs$Pericentral <- cv_genes
mySigs$Periportal
[1] "Saa2;Saa1-1" "HAMP" "APOA1"
[4] "APOC2" "CRYL1" "AMY1A;AMY1C;AMY1B;AMY2A;AMY2B"
[7] "MT-ATP6" "UROC1" "APOA2"
[10] "MT-CO3"
$Pericentral
[1] "FETUB" "HMGCS1" "CYP2E1" "GLUD1;GLUD2" "CYP1A2" "RGN" "INMT"
[8] "COMT" "FDPS" "SPR-1" Add these as gene signatures
sobj <- AddModuleScore_UCell(sobj, features = mySigs, assay = "SCT")
signature.names <- paste0(names(mySigs), "_UCell")
VlnPlot(sobj, features = signature.names, group.by = "SCT_snn_res.0.2")
SpatialFeaturePlot(sobj,
features = signature.names,
images = 'slice1')
SpatialFeaturePlot(sobj,
features = signature.names,
images = 'slice1.1')
Create figures of spatial plots with signatures
plot1 <- SpatialFeaturePlot(sobj,
features = "Periportal_UCell",
images = 'slice1')plot2 <- SpatialFeaturePlot(sobj,
features = "Periportal_UCell",
images = 'slice1.1')pdf("./figures/spatial/periportalSig_spatial_UCell.pdf")
plot1 + plot2
dev.off()null device
1 plot1 <- SpatialFeaturePlot(sobj,
features = "Pericentral_UCell",
images = 'slice1')plot2 <- SpatialFeaturePlot(sobj,
features = "Pericentral_UCell",
images = 'slice1.1')pdf("./figures/spatial/pericentralSig_spatial_UCell.pdf")
plot1 + plot2
dev.off()null device
1 Create heatmap with signature genes
plot <- DoHeatmap(sobj,
features = c(pp_genes, cv_genes),
angle = 0,
size = 3)
plot
pdf("./figures/spatial/zoneSigs_byClust_heatmap.pdf")plot
dev.off()png
2 
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